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Profiling cellular heterogeneity in formalin-fixed paraffin-embedded (FFPE) tissues is key to characterizing clinical specimens for biomarkers, therapeutic targets, and drug responses. Here, we optimize methods for isolating intact nuclei and single nucleus RNA-Seq from FFPE tissues in the mouse brain, and demonstrate a pilot application to a human clinical specimen of lung adenocarcinoma. Our method opens the way to broad applications of snRNA-Seq to archival tissues, including clinical samples.

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

Adipose tissue is usually classified on the basis of its function as white, brown or beige (brite)1. It is an important regulator of systemic metabolism, as shown by the fact that dysfunctional adipose tissue in obesity leads to a variety of secondary metabolic complications2,3. In addition, adipose tissue functions as a signalling hub that regulates systemic metabolism through paracrine and endocrine signals4. Here we use single-nucleus RNA-sequencing (snRNA-seq) analysis in mice and humans to characterize adipocyte heterogeneity. We identify a rare subpopulation of adipocytes in mice that increases in abundance at higher temperatures, and we show that this subpopulation regulates the activity of neighbouring adipocytes through acetate-mediated modulation of their thermogenic capacity. Human adipose tissue contains higher numbers of cells of this subpopulation, which could explain the lower thermogenic activity of human compared to mouse adipose tissue and suggests that targeting this pathway could be used to restore thermogenic activity.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases., A set of ready-to-use tools for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq facilitates the implementation of single-cell technologies in clinical settings and the construction of single-cell tumor atlases.

Tumor heterogeneity is a major challenge for oncology drug discovery and development. Understanding of the spatial tumor landscape is key to identifying new targets and impactful model systems. Here, we test the utility of spatial transcriptomics (ST) for oncology discovery by profiling 40 tissue sections and 80,024 capture spots across a diverse set of tissue types, sample formats, and RNA capture chemistries. We verify the accuracy and fidelity of ST by leveraging matched pathology analysis, which provides a ground truth for tissue section composition. We then use spatial data to demonstrate the capture of key tumor depth features, identifying hypoxia, necrosis, vasculature, and extracellular matrix variation. We also leverage spatial context to identify relative cell-type locations showing the anti-correlation of tumor and immune cells in syngeneic cancer models. Lastly, we demonstrate target identification approaches in clinical pancreatic adenocarcinoma samples, highlighting tumor intrinsic biomarkers and paracrine signaling.

Understanding the function of genes and their regulation in tissue homeostasis and disease requires knowing the cellular context in which genes are expressed in tissues across the body. Single cell genomics allows the generation of detailed cellular atlases in human tissues, but most efforts are focused on single tissue types. Here, we establish a framework for profiling multiple tissues across the human body at single-cell resolution using single nucleus RNA-Seq (snRNA-seq), and apply it to 8 diverse, archived, frozen tissue types (three donors per tissue). We apply four snRNA-seq methods to each of 25 samples from 16 donors, generating a cross-tissue atlas of 209,126 nuclei profiles, and benchmark them vs. scRNA-seq of comparable fresh tissues. We use a conditional variational autoencoder (cVAE) to integrate an atlas across tissues, donors, and laboratory methods. We highlight shared and tissue-specific features of tissue-resident immune cells, identifying tissue-restricted and non-restricted resident myeloid populations. These include a cross-tissue conserved dichotomy between LYVE1- and HLA class II-expressing macrophages, and the broad presence of LAM-like macrophages across healthy tissues that is also observed in disease. For rare, monogenic muscle diseases, we identify cell types that likely underlie the neuromuscular, metabolic, and immune components of these diseases, and biological processes involved in their pathology. For common complex diseases and traits analyzed by GWAS, we identify the cell types and gene modules that potentially underlie disease mechanisms. The experimental and analytical frameworks we describe will enable the generation of large-scale studies of how cellular and molecular processes vary across individuals and populations.

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

This protocol describes amethodbased on work by Drokhlyansky et al.for nuclei isolation from frozen tissue.It can be used on both healthy and disease tissues and is compatible with droplet-based single-nucleus RNA-Seq technologySlyper et al. This method is part of a toolbox for processing frozen tissue samples forsingle-nucleus RNA-Seq, including the CST (this protocol), TST and NST protocols (all available inprotocols.io). We recommend users to test all three protocols on their tissue type of interest and perform side-by-side comparison of the data generated. A description of the complete toolbox andguidance for testing and selecting methods from the toolbox for processing other tumors can be found in Slyper et al. For the Human Tumor Atlas Pilot Project (HTAPP), the CST-nuclei isolation method was used to profile pediatric glioma frozen samples. It was also tested on metastatic breast cancer, ovarian cancer, pediatric sarcoma, and pediatric neuroblastoma frozen samples. For these cancer types, however, TST was the protocol of choice.

This protocol describes amethodbased on work by Drokhlyansky et al.for nuclei isolation from frozen tissue.It can be used on both healthy and disease tissues and is compatible with droplet-based single-nucleus RNA-Seq technologySlyper et al. This method is part of a toolbox for processing frozen tissue samples forsingle-nucleus RNA-Seq, including the TST (this protocol), CST and NST protocols (all available inprotocols.io). We recommend users to test all three protocols on their tissue type of interest and perform side-by-side comparison of the data generated. A description of the complete toolbox andguidance for testing and selecting methods from the toolbox for processing other tumors can be found in Slyper et al. For the Human Tumor Atlas Pilot Project (HTAPP), the TST-nuclei isolation method was used to profile metastatic breast cancer, ovarian cancer, pediatric neuroblastoma and pediatric sarcoma frozen samples.

This protocol describes a nuclei isolation method for frozen tissues based on the previously published protocol by Gao et al. and modified by Drokhlyansky et al. It can be used on both healthy and disease tissues and is compatible with droplet-based single-nucleus RNA-Seq technologySlyper et al. This method is part of a toolbox for processing frozen tissue samples forsingle-nucleus RNA-Seq, including the NST (this protocol), CST and TST protocols (all available inprotocols.io). We recommend users to test all three protocols on their tissue type of interest and perform side-by-side comparison of the data generated. A description of the complete toolbox andguidance for testing and selecting methods from the toolbox for processing other tumors can be found in Slyper et al. For the Human Tumor Atlas Pilot Project (HTAPP), this protocol was tested on metastatic breast cancer, ovarian cancer and pediatric neuroblastoma frozen samples. For these cancer types, however, TST was the protocol of choice. When tested on HTAPP samples, NST, in general, underperformed compared to TST and CST based on several QC parameters.

A molecular classification of pancreatic ductal adenocarcinoma (PDAC) that informs clinical management remains elusive. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-like, and (2) basal-like. Basal-like tumors were associated with worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for banked frozen PDAC specimens and studied a cohort of untreated resected primary tumors (n ~ 20). Gene expression programs learned across malignant cell and cancer-associated fibroblast (CAF) profiles uncovered a clinically-relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Digital spatial profiling revealed an association between malignant cells expressing basal-like programs and greater immune infiltration with relatively fewer macrophages, whereas those exhibiting classical-like programs were linked to inflammatory CAFs and macrophage-predominant microniches. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment impacts residual tumor cells and their interactions with other cell types in the tumor microenvironment to identify additional therapeutic vulnerabilities that can be exploited. Towards this end, we performed snRNA-seq on an unmatched cohort of neoadjuvant-treated resected primary tumors (n ~ 25) with most cases involving FOLFIRINOX chemotherapy followed by chemoradiation. Remarkably, the quality of single-nucleus mRNA profiles was comparable between heavily pre-treated and untreated specimens. We identified differentially expressed genes between treated and untreated samples to infer cell-type specific reprogramming in the residual tumor. This analysis revealed that in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into compartment-specific therapies. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Payman Yadollahpour, Jason Reeves, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Orr Ashenberg, Clifton Rodrigues, Domenic Abbondanza, Toni Delorey, Devan Phillips, Jorge Roldan, Debora Ciprani, Marina Kern, Jaimie L. Barth, Daniel R. Zollinger, Kit Fuhrman, Robin Fropf, Joseph Beechem, Colin Weekes, Cristina R. Ferrone, Jennifer Y. Wo, Theodore S. Hong, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Mari Mino-Kenudson, Carlos Fernandez-del- Castillo, Andrew S. Liss, David T. Ting, Tyler Jacks, Aviv Regev. Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 94.

This protocol describes a robust and easy method for nuclei isolation for frozen tissues based on unpublished work by Drokhlyansky et al. This protocol is compatible with 10X droplet-based single-cell technology. This method is part of a toolbox for processing frozen tissue samples, including the TST (this protocol), CST and NST protocols (all available in protocols.io). We recommend users to test all three protocols on their tissue type of interest, and perform side-by-side comparison of the data generated. For the HTAPP project, this protocol was tested and validated for metastatic breast cancer, ovarian cancer, pediatric neuroblastoma and pediatric sarcoma frozen samples.

This protocol describes a robust and easy method for nuclei isolation for frozen tissues based on unpublished work by Drokhlyansky et al. This protocol is compatible with 10X droplet-based single-cell technology. This method is part of a toolbox for processing frozen tissue samples, including the CST (this protocol), TST and NST protocols (all available in protocols.io). We recommend users to test all three protocols on their tissue type of interest, and perform side-by-side comparison of the data generated. For the HTAPP project, this protocol was tested and validated for pediatric glioma frozen samples. This protocol was also tested on metastatic breast cancer, ovarian cancer, pediatric sarcoma, and pediatric neuroblastoma frozen samples. For these cancer types, however, TST was the protocol of choice.

This protocol describes a nuclei isolation method for frozen tissues based on the previously published protocol by Gao et al. and modified Drokhlyansky et al (unpublished). This protocol is compatible with 10X droplet-based single-cell technology. This method is part of a toolbox for processing frozen tissue samples, including the NST (this protocol), CST and TST protocols (all available in protocols.io). We recommend users to test all three protocols on their tissue type of interest, and perform side-by-side comparison of the data generated. For the HTAPP project, this protocol was tested on metastatic breast cancer, ovarian cancer and pediatric neuroblastoma frozen samples. For these cancer types, however, TST was the protocol of choice. When tested on HTAPP samples, NST, in general, underperformed compared to TST and CST, based on several QC parameters.

This protocol describes a nuclei isolation method based on the previously publishedDroNc-seq step-by-step protocol (linkbelow) with some modifications and instructions for loading the nuclei on 10X genomics. For the HTAPP project, this protocol was tested on pediatric neuroblastoma samples. For this cancer type, however, the TST nuclei isolation method was the protocol of choice. The TST method is part of a toolbox for processing frozen tissue samples, including the TST, CST and TST protocols (all available in protocols.io). The EZ method was developed for brain tissue (link), and when tested on HTAPP samples, it underperformed compared to TST, CST and NST, based on several QC parameters. We recommend users to test all protocols on their tissue type of interest, and perform side-by-side comparison of the data generated.

This protocol describes a modified version of Smart-Seq2 (Trombetta et al.) with altered steps to obtain full-length transcriptomic data from single nuclei.

The enteric nervous system (ENS) coordinates diverse functions in the intestine but has eluded comprehensive molecular characterization because of the rarity and diversity of cells. Here we develop two methods to profile the ENS of adult mice and humans at single-cell resolution: RAISIN RNA-seq for profiling intact nuclei with ribosome-bound mRNA and MIRACL-seq for label-free enrichment of rare cell types by droplet-based profiling. The 1,187,535 nuclei in our mouse atlas include 5,068 neurons from the ileum and colon, revealing extraordinary neuron diversity. We highlight circadian expression changes in enteric neurons, show that disease-related genes are dysregulated with aging, and identify differences between the ileum and proximal/distal colon. In humans, we profile 436,202 nuclei, recovering 1,445 neurons, and identify conserved and species-specific transcriptional programs and putative neuro-epithelial, neuro-stromal, and neuro-immune interactions. The human ENS expresses risk genes for neuropathic, inflammatory, and extra-intestinal diseases, suggesting neuronal contributions to disease.

Molecular subtyping of pancreatic ductal adenocarcinoma (PDAC) remains in its nascent stages and does not currently inform clinical management or therapeutic development. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-pancreatic, encompassing a spectrum of pancreatic lineage precursors, and (2) basal-like/squamous/quasi-mesenchymal, characterized by loss of endodermal identity and aberrations in chromatin modifiers. Basal-like tumors were associated with poorer responses to chemotherapy and worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment reprograms residual tumor cells to identify additional therapeutic vulnerabilities that can be exploited in combination with neoadjuvant CRT. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors (n = 15) and those that received neoadjuvant CRT (n = 11). Gene expression programs learned across malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification (median survival: 11.2 months in highest risk group to 44.7 months in lowest risk group) compared to prior classifications. Moreover, in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. These results suggest that differentiated endodermal phenotypes are only prevalent enough to be detected under treatment selection pressure and when observed in treatment-naïve bulk studies, may reflect normal cell contamination. Spatially-resolved transcriptomics revealed an association between malignant cells expressing basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to distinct therapeutic susceptibilities. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, Jason Reeves, Daniel R. Zollinger, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Clifton Rodrigues, Domenic Abbondanza, Debora Ciprani, Jennifer Y. Wo, Theodore S. Hong, Andrew J. Aguirre, Orit Rozenblatt-Rosen, Mari Mino-Kenudson, Carlos Fernandez-del Castillo, Andrew S. Liss, Tyler E. Jacks, Aviv Regev. Single-nucleus and spatial transcriptomics of archival pancreatic ductal adenocarcinoma reveals multi-compartment reprogramming after neoadjuvant treatment [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-007.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

4633 Background: Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease and existing molecular subtypes do not inform clinical decisions. Previously identified bulk transcriptomic subtypes of PDAC were often unintentionally driven by “contaminating” stroma. RNA extraction from pancreatic tissue is difficult and prior single-cell RNA-seq efforts have been limited by suboptimal dissociation/RNA quality and poor performance in the setting of neoadjuvant treatment. We developed a robust single-nucleus RNA-seq (sNuc-seq) technique compatible with frozen archival PDAC specimens. Methods: Single nuclei suspensions were extracted from frozen primary PDAC specimens (n = 27) derived from patients with (borderline)-resectable PDAC who underwent surgical resection with or without neoadjuvant chemoradiotherapy (CRT). Approximately 170,000 nuclei were processed with the 10x Genomics Single Cell 3’ v3 pipeline and gene expression libraries were sequenced (Illumina HiSeq X). Results: Distinct nuclei clusters with gene expression profiles/inferred copy number variation analysis consistent with neoplastic, acinar, ductal, fibroblast, endothelial, endocrine, lymphocyte, and myeloid populations were identified with proportions similar to corresponding multiplexed ion beam imaging. Non-negative matrix factorization revealed intra-tumoral heterogeneity shared across patients. Neoplastic cells featured eight distinct transcriptional topics characterized by developmental (epithelial, mesenchymal, endoderm progenitor, neural progenitor) and environmental (anabolic, catabolic, cycling, hypoxic) programs. CAFs exhibited four different transcriptional topics (activated/desmoplastic, myofibroblast, neurogenic, osteochondral). Differential gene expression and gene set enrichment analyses demonstrated that CRT was associated with an enrichment in myogenic programs in CAFs, activation pathways in immune cells, and type I/II interferons in malignant cells. CRT was also associated with a depletion in developmental programs within malignant cells. Conclusions: We uncovered significant intratumoral heterogeneity and treatment-associated differences in the malignant, fibroblast, and immune compartments of PDAC using sNuc-seq. Deconvolution of clinically-annotated bulk RNA-seq cohorts and characterization of intercellular interactions with receptor-ligand analysis and spatial transcriptomics are ongoing.

Single-nucleus RNA-Seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate, including frozen clinical samples. This opens the way, in principle, to large studies, such as those required for human genetics, clinical trials, or precise cell atlases of large organs. However, such applications are currently limited by batch effects, sequential processing, and costs. To address these challenges, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies against the nuclear pore complex to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled in multiplex with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter the recovered transcriptome profiles. We further developed demuxEM, a novel computational tool that robustly detects inter-sample nucleus multiplets and assigns singlets to their samples of origin by antibody barcodes, and validated its accuracy using gender-specific gene expression, species-mixing and natural genetic variation. Nucleus hashing significantly reduces cost per nucleus, recovering up to about 5 times as many single nuclei per microfluidc channel. Our approach provides a robust technique for diverse studies including tissue atlases of isogenic model organisms or from a single larger human organ, multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.

Vesicular stomatitis virus has been shown to bud basolaterally, and the matrix protein, but not glycoprotein, was proposed to mediate this asymmetry. Using polarized T84 monolayers, we demonstrate that no single viral protein is sufficient for polarized budding. Particles are released from the apical and basolateral surfaces and are indistinguishable, indicating that there is no apical assembly defect. We propose that aspects of host cell polarity create a more efficient budding process at the basolateral surface.

Vertebrate photoreceptors are among the most metabolically active cells, exhibiting a high rate of ATP consumption. This is coupled with a high anabolic demand, necessitated by the diurnal turnover of a specialized membrane-rich organelle, the outer segment, which is the primary site of phototransduction. How photoreceptors balance their catabolic and anabolic demands is poorly understood. Here, we show that rod photoreceptors in mice rely on glycolysis for their outer segment biogenesis. Genetic perturbations targeting allostery or key regulatory nodes in the glycolytic pathway impacted the size of the outer segments. Fibroblast growth factor signaling was found to regulate glycolysis, with antagonism of this pathway resulting in anabolic deficits. These data demonstrate the cell autonomous role of the glycolytic pathway in outer segment maintenance and provide evidence that aerobic glycolysis is part of a metabolic program that supports the biosynthetic needs of a normal neuronal cell type. DOI: http://dx.doi.org/10.7554/eLife.25946.001, eLife digest Living cells need building materials and energy to grow and carry out their activities. Most cells in the body use sugars like glucose for these purposes. In a process known as glycolysis, cells break down glucose into molecules that are eventually converted to carbon dioxide and water to form the chemical ATP – the cellular currency for energy. Developing cells that have not yet fully specialized, and rapidly dividing cells, like cancer cells, consume large amounts of glucose via aerobic glycolysis (also known as the Warburg effect) as they require high levels of energy and building materials. As cells become more specialized and divide less often, they have a reduced need for building blocks, and adjust their consumption and breakdown of glucose accordingly. One exception is the photoreceptor cells, found in the light-sensitive part of our eyes. Although these specialized cells do not divide, they still need a lot of energy and building blocks to constantly renew their light-sensing and processing structures, and to capture and convert the information from the environment into signals. Previous research has shown that the eye also uses the Warburg effect. However, until now, it was not known whether the photoreceptors or other cells in the eye carry out this form of glycolysis. Using genetic tools, Chinchore et al. analysed how the photoreceptor cells in mice used glucose. The experiments demonstrated that the photoreceptors do indeed carry out the Warburg effect. Chinchore et al. further discovered that the Warburg effect is regulated by the same key enzymes and signalling molecules that cancer cells use. This indicates that specialized cells like photoreceptors might choose to retain certain metabolic features of their precursor cells, if they need to. These findings provide new insight into how photoreceptors use glucose. The next step will be to understand how aerobic glycolysis is regulated in healthy eyes as well as in eyes that are affected by degenerating diseases, which may ultimately lead to new ways of treating blindness. DOI: http://dx.doi.org/10.7554/eLife.25946.002

The brain has a tightly regulated environment that protects neurons and limits inflammation, designated "immune privilege." However, there is not an absolute lack of an immune response. We tested the ability of the brain to initiate an innate immune response to a virus, which was directly injected into the brain parenchyma, and to determine whether this response could limit viral spread. We injected vesicular stomatitis virus (VSV), a transsynaptic tracer, or naturally occurring VSV-derived defective interfering particles (DIPs), into the caudate-putamen (CP) and scored for an innate immune response and inhibition of virus spread. We found that the brain parenchyma has a functional type I interferon (IFN) response that can limit VSV spread at both the inoculation site and among synaptically connected neurons. Furthermore, we characterized the response of microglia to VSV infection and found that infected microglia produced type I IFN and uninfected microglia induced an innate immune response following virus injection.

The ability to detect and/or manipulate specific cell populations based upon the presence of intracellular protein epitopes would enable many types of studies and applications. Protein binders such as nanobodies (Nbs) can target untagged proteins (antigens) in the intracellular environment. However, genetically expressed protein binders are stable regardless of antigen expression, complicating their use for applications that require cell-specificity. Here, we created a conditional system in which the stability of an Nb depends upon an antigen of interest. We identified Nb framework mutations that can be used to rapidly create destabilized Nbs. Fusion of destabilized Nbs to various proteins enabled applications in living cells, such as optogenetic control of neural activity in specific cell types in the mouse brain, and detection of HIV-infected human cells by flow cytometry. These approaches are generalizable to other protein binders, and enable the rapid generation of single-polypeptide sensors and effectors active in cells expressing specific intracellular epitopes. DOI: http://dx.doi.org/10.7554/eLife.15312.001, eLife digest Biologists often wish to study the role of a particular cell type within an organism, but such studies are often not possible due to the lack of reagents that allow one to gain control of the cell type of interest. One method that can be used to detect and manipulate the cells that express specific proteins uses molecules called antibodies. An antibody can strongly bind to a specific part of a protein, and a diversity of antibodies that bind to different proteins can be isolated by animal immunization, or by using molecular or cell-based methods. Antibodies from camelid species (which include camels and llamas) are increasingly being used to detect and manipulate proteins in living cells. The variable region of these antibodies – also known as the nanobody – recognises the proteins that the antibody binds to, and often just this fragment of the antibody is used in protein detection experiments. However, nanobodies are stable even in cells that do not contain their target proteins, which makes it difficult to use nanobodies to study just a specific cell type within an organism. Tang, Drokhlyansky et al. have now developed a way of engineering the sequence of a nanobody so that it is broken down in living cells unless it is bound to its protein target inside the cell. Any protein that is tethered to the engineered nanobody is also broken down. For example, some tethered proteins with useful biological activities are fluorescent proteins and enzymes that can modify DNA. When one of these engineered nanobodies binds to a protein target of interest, the activity of the nanobody-tethered protein can be turned on in just those cells that produce the targeted protein. Thus, this strategy of engineering allows “conditionally stable” tools to be generated. A core set of sequence alterations can be used to modify different nanobodies that target different proteins. Tang, Drokhlyansky et al. have demonstrated the uses of several of the resulting conditionally stable nanobodies. In one application, the nanobodies were used to target specific cell types in the mouse brain in a way that allowed the activity of these cells to be controlled by light. Another application of the technique enables live human cells that have been infected with HIV to be detected and isolated. The conditionally stable nanobody tools can be used to detect and manipulate cells that express any protein for which a camelid antibody exists. Tang, Drokhlyansky et al. therefore hope that biologists who work in a wide range of fields will find the tools useful for studying many different types of organisms and biological processes. DOI: http://dx.doi.org/10.7554/eLife.15312.002

High-grade tumors in the brain are among the deadliest of cancers. Here, we took a promising oncolytic virus, vesicular stomatitis virus (VSV), and tested the hypothesis that the neurotoxicity associated with the virus could be eliminated without blocking its oncolytic potential in the brain by replacing the neurotropic VSV glycoprotein with the glycoprotein from one of five different viruses, including Ebola virus, Marburg virus, lymphocytic choriomeningitis virus (LCMV), rabies virus, and Lassa virus. Based on in vitro infections of normal and tumor cells, we selected two viruses to test in vivo . Wild-type VSV was lethal when injected directly into the brain. In contrast, a novel chimeric virus (VSV-LASV-GPC) containing genes from both the Lassa virus glycoprotein precursor (GPC) and VSV showed no adverse actions within or outside the brain and targeted and completely destroyed brain cancer, including high-grade glioblastoma and melanoma, even in metastatic cancer models. When mice had two brain tumors, intratumoral VSV-LASV-GPC injection in one tumor (glioma or melanoma) led to complete tumor destruction; importantly, the virus moved contralaterally within the brain to selectively infect the second noninjected tumor. A chimeric virus combining VSV genes with the gene coding for the Ebola virus glycoprotein was safe in the brain and also selectively targeted brain tumors but was substantially less effective in destroying brain tumors and prolonging survival of tumor-bearing mice. A tropism for multiple cancer types combined with an exquisite tumor specificity opens a new door to widespread application of VSV-LASV-GPC as a safe and efficacious oncolytic chimeric virus within the brain. IMPORTANCE Many viruses have been tested for their ability to target and kill cancer cells. Vesicular stomatitis virus (VSV) has shown substantial promise, but a key problem is that if it enters the brain, it can generate adverse neurologic consequences, including death. We tested a series of chimeric viruses containing genes coding for VSV, together with a gene coding for the glycoprotein from other viruses, including Ebola virus, Lassa virus, LCMV, rabies virus, and Marburg virus, which was substituted for the VSV glycoprotein gene. Ebola and Lassa chimeric viruses were safe in the brain and targeted brain tumors. Lassa-VSV was particularly effective, showed no adverse side effects even when injected directly into the brain, and targeted and destroyed two different types of deadly brain cancer, including glioblastoma and melanoma.

SummaryThe ocular motility disorder “Congenital fibrosis of the extraocular muscles type 1” (CFEOM1) results from heterozygous mutations altering the motor and third coiled-coil stalk of the anterograde kinesin, KIF21A. We demonstrate that Kif21a knockin mice harboring the most common human mutation develop CFEOM. The developing axons of the oculomotor nerve’s superior division stall in the proximal nerve; the growth cones enlarge, extend excessive filopodia, and assume random trajectories. Inferior division axons reach the orbit but branch ectopically. We establish a gain-of-function mechanism and find that human motor or stalk mutations attenuate Kif21a autoinhibition, providing in vivo evidence for mammalian kinesin autoregulation. We identify Map1b as a Kif21a-interacting protein and report that Map1b−/− mice develop CFEOM. The interaction between Kif21a and Map1b is likely to play a critical role in the pathogenesis of CFEOM1 and highlights a selective vulnerability of the developing oculomotor nerve to perturbations of the axon cytoskeleton.